Uses of Graphical Causal Models in the Social Science - Single View

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Type of Course	Seminar	Number	4232111
Hours per week in term	2	Term	WiSe 2019/20
Department	Sozialwissenschaften	Language	englisch
application period	01.10.2019 - 20.11.2019 enrollment

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		Day	Time	Frequency	Duration	Room	Lecturer	Canceled/rescheduled on	Max. participants
	Seminar	-	to	wöchentlich	at		Prof. Dr. Kohler		25

Description	Achtung Raumänderung! Das Seminar findet ab sofort im Büro von Prof. Kohler 3.01.122 statt. Graphical Causal Models in the form of "Directed Acyclic Graphs" (DAGs) have gained enormous attraction among empirical social researchers in recent years. DAGs can be used to pinpoint a research design necessary to identify a causal effect, but also to understand the interpretation of conditional associations between variables. They can be also used to deduce non-trivial testable implications of the researchers assumption of the entire data generating under study. Finally DAGs help to understand the theoretical assumptions underlying advanced statistical techniques such as instrumental variable regression or matching. The seminar introduces DAGs and and applies them as a tool to understand and criticize recently published empirical studies. The example studies will be selected from papers published in the European Sociological Review and the American Sociological Review.
Literature	Elwert, Felix (2014): Graphical Causal Models. s. 244--273 in Morgan, S: Handbook of Causal Analysis for Social Research. Springer.

Description

Achtung Raumänderung!

Das Seminar findet ab sofort im Büro von Prof. Kohler 3.01.122 statt.

Graphical Causal Models in the form of "Directed Acyclic Graphs" (DAGs) have gained enormous attraction among empirical social researchers in recent years. DAGs can be used to pinpoint a research design necessary to identify a causal effect, but also to understand the interpretation of conditional associations between variables. They can be also used to deduce non-trivial testable implications of the researchers assumption of the entire data generating under study. Finally DAGs help to understand the theoretical assumptions underlying advanced statistical techniques such as instrumental variable regression or matching.

The seminar introduces DAGs and and applies them as a tool to understand and criticize recently published empirical studies. The example studies will be selected from papers published in the European Sociological Review and the American Sociological Review.

Literature

Elwert, Felix (2014): Graphical Causal Models. s. 244--273 in Morgan, S: Handbook of Causal Analysis for Social Research. Springer.

Structure Tree

Lecture not found in this Term. Lecture is in Term WiSe 2019/20 , Currentterm: SoSe 2024